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Designing steganographic distortion using directional filters
 In Fourth IEEE International Workshop on Information Forensics and Security
, 2012
"... This paper presents a new approach to defining additive steganographic distortion in the spatial domain. The change in the output of directional highpass filters after changing one pixel is weighted and then aggregated using the reciprocal Hölder norm to define the individual pixel costs. In contra ..."
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Cited by 21 (15 self)
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This paper presents a new approach to defining additive steganographic distortion in the spatial domain. The change in the output of directional highpass filters after changing one pixel is weighted and then aggregated using the reciprocal Hölder norm to define the individual pixel costs. In contrast to other adaptive embedding schemes, the aggregation rule is designed to force the embedding changes to highly textured or noisy regions and to avoid clean edges. Consequently, the new embedding scheme appears markedly more resistant to steganalysis using rich models. The actual embedding algorithm is realized using syndrometrellis codes to minimize the expected distortion for a given payload. 1.
Message in a bottle: Sailing past censorship
 In 29th Annual Computer Security Applications Conference – ACSAC 2013
, 2013
"... Exploiting recent advances in monitoring technology and the drop of its costs, authoritarian and oppressive regimes are tightening the grip around the virtual lives of their citizens. Meanwhile, the dissidents, oppressed by these regimes, are organizing online, cloaking their activity with anticens ..."
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Cited by 11 (0 self)
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Exploiting recent advances in monitoring technology and the drop of its costs, authoritarian and oppressive regimes are tightening the grip around the virtual lives of their citizens. Meanwhile, the dissidents, oppressed by these regimes, are organizing online, cloaking their activity with anticensorship systems that typically consist of a network of anonymizing proxies. The censors have become well aware of this, and they are systematically finding and blocking all the entry points to these networks. So far, they have been quite successful. We believe that, to achieve resilience to blocking, anticensorship systems must abandon the idea of having a limited number of entry points. Instead, they should establish first contact in an online location arbitrarily chosen by each of their users. To explore this idea, we have developed Message In A Bottle, a protocol where any blog post becomes a potential “drop point ” for hidden messages. We have developed and released a proofofconcept application using our system, and demonstrated its feasibility. To block this system, censors are left with a needleinahaystack problem: Unable to identify what bears hidden messages, they must block everything, effectively disconnecting their own network from a large part of the Internet. This, hopefully, is a cost too high to bear. 1
Moving Steganography and Steganalysis from the Laboratory into the Real World
"... There has been an explosion of academic literature on steganography and steganalysis in the past two decades. With a few exceptions, such papers address abstractions of the hiding and detection problems, which arguably have become disconnected from the real world. Most published results, including b ..."
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Cited by 9 (7 self)
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There has been an explosion of academic literature on steganography and steganalysis in the past two decades. With a few exceptions, such papers address abstractions of the hiding and detection problems, which arguably have become disconnected from the real world. Most published results, including by the authors of this paper, apply “in laboratory conditions ” and some are heavily hedged by assumptions and caveats; significant challenges remain unsolved in order to implement good steganography and steganalysis in practice. This position paper sets out some of the important questions which have been left unanswered, as well as highlighting some that have already been addressed successfully, for steganography and steganalysis to be used in the real world.
MULTIVARIATE GAUSSIAN MODEL FOR DESIGNING ADDITIVE DISTORTION FOR STEGANOGRAPHY
"... Currently, the most successful approach to steganography in empirical objects, such as digital media, is to cast the embedding problem as source coding with a fidelity constraint. The sender specifies the costs of changing each cover element and then embeds a given payload by minimizing the total em ..."
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Cited by 8 (5 self)
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Currently, the most successful approach to steganography in empirical objects, such as digital media, is to cast the embedding problem as source coding with a fidelity constraint. The sender specifies the costs of changing each cover element and then embeds a given payload by minimizing the total embedding cost. Since efficient practical codes exist that embed near the rate–distortion bound, the remaining task left to the steganographer is the fidelity measure – the choice of the costs. In the past, the costs were obtained either in an ad hoc manner or determined from the effects of embedding in a chosen feature space. In this paper, we adopt a different strategy in which the cover is modeled as a sequence of independent but not necessarily identically distributed quantized Gaussians and the embedding change probabilities are derived to minimize the total KL divergence within the chosen model for a given embedding operation and payload. Despite the simplicity of the adopted model, the resulting stegosystem exhibits security that is comparable to current stateoftheart methods methods across a wide range of payloads. Index Terms — Steganography, multivariate Gaussian cover, additive distortion function, syndrometrellis codes, steganalysis 1.
Universal Distortion Function for Steganography in an Arbitrary Domain
, 2013
"... Currently, the most successful approach to steganography in empirical objects, such as digital media, is to embed the payload while minimizing a suitably defined distortion function. The design of the distortion is essentially the only task left to the steganographer since efficient practical codes ..."
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Cited by 7 (5 self)
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Currently, the most successful approach to steganography in empirical objects, such as digital media, is to embed the payload while minimizing a suitably defined distortion function. The design of the distortion is essentially the only task left to the steganographer since efficient practical codes exist that embed near the payload–distortion bound. The practitioner’s goal is to design the distortion to obtain a scheme with a high empirical statistical detectability. In this paper, we propose a universal distortion design called UNIWARD (UNIversal WAvelet Relative Distortion) that can be applied for embedding in an arbitrary domain. The embedding distortion is computed as a sum of relative changes of coefficients in a directional filter bank decomposition of the cover image. The directionality forces the embedding changes to such parts of the cover object that are difficult to model in multiple directions, such as textures or noisy regions, while avoiding smooth regions or clean edges. We demonstrate experimentally using rich models as well as targeted attacks that steganographic methods built using UNIWARD match or outperform the current state of the art in the spatial domain, JPEG domain, and sideinformed JPEG domain. 1
Further Study on the Security of SUNIWARD
"... Recently, a new steganographic method was introduced that utilizes a universal distortion function called UNIWARD. The distortion between the cover and stego image is computed as a sum of relative changes of wavelet coefficients representing both images. As already pointed out in the original publi ..."
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Cited by 3 (2 self)
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Recently, a new steganographic method was introduced that utilizes a universal distortion function called UNIWARD. The distortion between the cover and stego image is computed as a sum of relative changes of wavelet coefficients representing both images. As already pointed out in the original publication, the selection channel of the spatial version of UNIWARD (the version that hides messages in pixel values called SUNIWARD) exhibits unusual properties – in highly textured and noisy regions the embedding probabilities form interleaved streaks of low and high embedding probability. While the authors of UNIWARD themselves hypothesized that such an artifact in the embedding probabilities may jeopardize its security, experiments with stateoftheart rich models did not reveal any weaknesses. Using the fact that the cover embedding probabilities can be approximately estimated from the stego image, we introduce the novel concept of contentselective residuals and successfully attack SUNIWARD. We also show that this attack, which is made possible by a faulty probabilistic selection channel, can be prevented by properly adjusting the stabilizing constant in the UNIWARD distortion function.
Batch steganography in the real world
 In Proceedings of the 14th ACM Multimedia & Security Workshop
, 2012
"... We examine the universal pooled steganalyzer of [15] in two respects. First, we confirm that the method is applicable to a number of different steganographic embedding methods. Second, we consider the converse problem of how to spread payload between multiple covers, by testing different payload al ..."
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Cited by 1 (1 self)
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We examine the universal pooled steganalyzer of [15] in two respects. First, we confirm that the method is applicable to a number of different steganographic embedding methods. Second, we consider the converse problem of how to spread payload between multiple covers, by testing different payload allocation strategies against the universal steganalyzer. We focus on practical options which can be implemented without new software or expert knowledge, and we test on realworld data. Concentration of payload into the minimal number of covers is consistently the least detectable option. We present additional investigations which explain this phenomenon, uncovering a nonlinear relationship between embedding distortion and payload. We conjecture that this is an unavoidable consequence of blind steganalysis. This is significant for both batch steganography and pooled steganalysis.
Optimizing Pixel Predictors for Steganalysis
"... A standard way to design steganalysis features for digital images is to choose a pixel predictor, use it to compute a noise residual, and then form joint statistics of neighboring residual samples (cooccurrence matrices). This paper proposes a general datadriven approach to optimizing predictors f ..."
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A standard way to design steganalysis features for digital images is to choose a pixel predictor, use it to compute a noise residual, and then form joint statistics of neighboring residual samples (cooccurrence matrices). This paper proposes a general datadriven approach to optimizing predictors for steganalysis. First, a local pixel predictor is parametrized and then its parameters are determined by solving an optimization problem for a given sample of cover and stego images and a given cover source. Our research shows that predictors optimized to detect a specific case of steganography may be vastly different than predictors optimized for the cover source only. The results indicate that optimized predictors may improve steganalysis by a rather nonnegligible margin. Furthermore, we construct the predictors sequentially – having optimized k predictors, design the k + 1st one with respect to the combined feature set built from all k predictors. In other words, given a feature space (image model) extend (diversify) the model in a selected direction (functional form of the predictor) in a way that maximally boosts detection accuracy.
1ContentAdaptive Steganography by Minimizing Statistical Detectability
"... Abstract—Most current steganographic schemes embed the secret payload by minimizing a heuristically defined distortion. Similarly, their security is evaluated empirically using classifiers equipped with rich image models. In this paper, we pursue an alternative approach based on a locallyestimate ..."
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Abstract—Most current steganographic schemes embed the secret payload by minimizing a heuristically defined distortion. Similarly, their security is evaluated empirically using classifiers equipped with rich image models. In this paper, we pursue an alternative approach based on a locallyestimated multivariate Gaussian cover image model that is sufficiently simple to derive a closedform expression for the power of the most powerful detector of contentadaptive LSB matching but, at the same time, complex enough to capture the nonstationary character of natural images.We show that when the cover model estimator is properly chosen, stateoftheart performance can be obtained. The closedform expression for detectability within the chosen model is used to obtain new fundamental insight regarding the performance limits of empirical steganalysis detectors built as classifiers. In particular, we consider a novel detectabilitylimited sender and estimate the secure payload of individual images. Index Terms—Adaptive steganography and steganalysis, hypothesis testing theory, information hiding, multivariate Gaussian, optimal detection. I.
A Review on Uniform Embedding For Efficient Jpeg
"... Steganography is the art and science of concealed communication with an aim to hide the secret messages in the cover medium. The concept of minimal distortion embedding has been accepted in development of the steganographic system, where a welldesigned distortion function plays an important role. M ..."
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Steganography is the art and science of concealed communication with an aim to hide the secret messages in the cover medium. The concept of minimal distortion embedding has been accepted in development of the steganographic system, where a welldesigned distortion function plays an important role. Majority of the steganographic methods for realtime digital media embed message communication by minimizing a suitably developed distortion function. This can be achieved by syndrome codes which give nearbest rate distortion function. Here the Uniform Embedding Distortion function will be used along with the Syndrome Trellis Coding. Thus, statistical detectability will be reduced thereby improving the security.